Brief Communication Allergy Asthma Immunol Res. 2015 January;7(1):83-87. http://dx.doi.org/10.4168/aair.2015.7.1.83 pISSN 2092-7355 • eISSN 2092-7363
Clinical Factors Affecting Discrepant Correlation Between Asthma Control Test Score and Pulmonary Function So Young Park, Sun-Young Yoon, Bomi Shin, Hyouk-Soo Kwon, Tae-Bum Kim, Hee-Bom Moon, You Sook Cho* Division of Allergy and Clinical Immunology, Department of Internal Medicine, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
The Asthma Control Test (ACT) score is widely used in asthma clinics, particularly with the recent emphasis on achievement and maintenance of optimal asthma control. However, this self-assessment score does not always correspond with lung function parameters, leading to uncertainty about each patient’s control status; therefore, we investigated the clinical characteristics that are associated with discrepant correlation between the ACT score and pulmonary function. The 252 adult asthmatic subjects were divided into 5 groups according to their changes in FEV1% predicted values and ACT scores between 2 consecutive visits three months apart. The data were retrospectively reviewed and several clinical variables were compared. Elderly, non-eosinophilic, non-atopic asthma patients were more likely to show paradoxical changes of pulmonary function and ACT score. Female patients were prone to report exaggerated changes of ACT score compared with baseline lung function and changes in FEV1 levels. This group was using more medications for rhinosinusitis. Male patients seemed less sensitive to changes in lung function. From these findings, we conclude that when assessing asthma control status, physicians should carefully consider patient age, gender, atopy status, blood eosinophil levels, and comorbidities along with their ACT scores and pulmonary function test results. Key Words: Asthma; asthma control test; pulmonary function test
INTRODUCTION The paradigm of asthma management has moved on from relieving acute attacks to achieving optimum asthma control, underpinned by improved understanding of the pathophysiology of the disease and prevalent use of inhaled corticosteroids.1 The need for a simple method for quantifying asthma control status by both patients and physicians has led to the creation of the ‘Asthma Control Test’ (ACT), a questionnaire that is currently used worldwide.2 The ACT is a self-report questionnaire that consists of 5 assessment items covering the previous four weeks: frequency of dyspnea, use of rescue medications, effect of asthma on daily functioning, frequency of night symptoms, and overall self-assessment of asthma control. Patients assess their subjective perception of their symptoms on a five-point scale for each item and the total score ranges from 0 to 25, with a higher score indicating well-controlled status.2 Since its introduction, the ACT has been validated for various applications in many countries including Korea.3,4 There is a consensus that the ACT reflects asthma control status in ways that objective clinical measures such as pulmonary function
may not evaluate.5 Although the results of pulmonary function tests, such as FEV1% predicted (FEV1) values, are considered one of the most important factors determining asthma control status, physicians are also aware of the fact that there is poor correlation between subjective reports of symptoms and pulmonary function at times.6,7 This discrepancy has caused substantial confusion in assessing asthma control status. Some patients show very good correlation between changes in ACT scores and FEV1, while some show no correlation between these 2 important clinical tools, which may mislead physicians in assessing asthma control status. This study was carried out to identify clinical characteristics of asthma patients that are associated with discrepant correlation between changes in ACT scores and FEV1 values over time. Correspondence to: You Sook Cho, MD, PhD, Division of Allergy and Clinical Immunology, Department of Internal Medicine, Asan Medical Center, University of Ulsan College of Medicine, 88 Olympic-ro 43-gil, Songpa-gu, Seoul 138-736, Korea. Tel: +82-2-3010-3285; Fax: +82-2-3010-6969; E-mail:
[email protected] Received: March 25, 2014; Revised: June 1, 2014; Accepted: August 7, 2014 •There are no financial or other issues that might lead to conflict of interest.
© Copyright The Korean Academy of Asthma, Allergy and Clinical Immunology • The Korean Academy of Pediatric Allergy and Respiratory Disease
http://e-aair.org 83
Volume 7, Number 1, January 2015
Park et al.
MATERIALS AND METHODS Study subjects A total of 252 asthmatic patients who visited the asthma clinic at Asan Medical Center from January 2009 to May 2011 were enrolled. The data were retrospectively reviewed. The study subjects were diagnosed with asthma by allergists based on the presence of asthma symptoms and documented evidence of reversible airway obstruction or airway hyperresponsiveness. The patients visited the clinic at least twice after diagnosis, 3 months apart, with reports of ACT scores and spirometry at both visits. This study was approved by the Institutional Review Board of Asan Medical Center. Study design With the measures of ACT and FEV1, we calculated ∆ACT and ∆FEV1 between each visit for every patient according to the following equation: ∆FEV1 (%) =
FEV1 (Visit 2) – FEV1 (Visit 1) ×100 FEV1 (Visit 1)
∆ACT=ACT (Visit 2) – ACT (Visit 1) Using ∆FEV1 and ∆ACT, we divided the study subjects into 5 groups as shown in Figure. Each group was defined as follows: group 1, positive correlation (FEV1 and ACT move in the same direction); group 2, paradoxical correlation (FEV1 and ACT move in opposite direction); group 3, no change (both FEV1 and ACT unchanged); group 4, ACT change without FEV1 change; and group 5, FEV1 change without ACT change. We defined ‘change of FEV1’ as change of at least 5% between the 2 visits and ‘change of ACT’ as change of at least two points between the 2 visits, as shown in Figure.
Figure. The distribution of the 5 groups of asthma patients according to their ∆FEV1 and ∆ACT.
http://e-aair.org 84
We compared these 5 groups in terms of several clinical parameters such as demographic data, pulmonary function, atopic status, and induced sputum analysis results. Rhinosinusitis medications taken by the patients such as antihistamine, decongestant and intranasal steroid were also assessed and compared. Statistical analysis Due to the small sample size, the Kruskal-Wallis test was used to compare continuous variables and Mann-Whitney U test was used to repeat tests for comparing 10 pairs of groups. Categorical variables were analyzed with Fisher’s exact test and Chisquare test. All statistical analyses were performed with SPSS software (Version 19.0; IBM).
RESULTS Data from 252 patients were retrieved. Patients were allocated into 1 of the 5 groups, and the patient groups were compared, as summarized in Table. The variables that showed significantly different features for the 5 groups were age, sex, prebronchodilator FEV1 at both visits, ACT scores at both visits, atopy status, blood eosinophil count and the number of rhinosinusitis medications. The mean patient age was highest in group 2 (59.23±17.23), and the male to female ratio was lowest in group 4 (38.2%) and highest in group 5 (69.1%). Prebronchodilator FEV1 at visit 1 and 2 was highest in group 4 (85.59±15.77 and 85.84±15.74). Group 2 had the lowest proportion of patients with atopy (15.4%) and lowest blood eosinophil counts (217.40±217.85/μL). The proportion of patients using more than 2 kinds of rhinosinusitis medications was the highest (47.3%) in group 4. Body mass index, smoking status, number of pack-years, total IgE level and sputum eosinophil numbers were not significantly different between the 5 groups. Baseline and followed ACT scores were higher at around 23 in groups 3 and 5 compared with other groups. Group 2, which showed a paradoxical correlation between FEV1 and ACT, was compared individually with every other group. Patients in group 2 had lower blood eosinophil counts, and the group contained fewer atopic patients. Although age difference was not statistically significant for all pairs tested, mean patient age was highest in group 2. In addition, we performed subgroup analysis of group 2, one that has increased FEV1 but decreased ACT and the other that has decreased FEV1 but increased ACT and we found no significant differences between these two subgroups (data not shown). Group 4, which showed ACT change without change in lung function, comprised more women than men and showed a tendency to use more medications for rhinosinusitis. Patients in group 4 had the highest prebronchodilator FEV1. Conversely, group 5, which showed FEV1 change without ACT change, had the highest proportion of men.
Allergy Asthma Immunol Res. 2015 January;7(1):83-87. http://dx.doi.org/10.4168/aair.2015.7.1.83
Asthma Control Test Score and Pulmonary Function
AAIR Table. Comparison of clinical parameters between the 5 patient groups
Age, year Men, n (%) BMI, kg/m2 FEV1% predicted, Visit 1 FEV1% predicted, Visit 2 ∆FEV1% predicted ACT, Visit 1 ACT, Visit 2 ∆ACT Smoking status, +/Pack-years Atopy status, +/Eosinophil count, /μL Total IgE, kU/L Sputum eosinophil, % ≥2 rhinosinusitis med
Group 1 (n=42)
Group 2 (n=26)
Group 3 (n=74)
Group 4 (n=55)
Group 5 (n=55)
P value*
52.95±15.99 17 (40.5)§ 24.83±5.25 75.40±20.03‡ 79.26±19.34‡ 13.17±12.40 19.12±4.70§,¶¶ 20.12±4.54§,¶¶ 5.38±3.56 19/23 (45.2) 7.82±17.73 18/24 (42.9)† 354.71±256.14† 455.44±694.79 19.82±25.98 16 (38.1)
59.23±17.23 13 (50.0) 23.78±3.34 81.04±16.03 81.77±15.56 8.19±4.43 19.77±4.44**,II 21.00±3.37**,II 5.00±3.68 14/12 (53.8) 12.06±16.51 4/22 (15.4)†,II,¶,** 217.40±217.85†,II,¶,** 570.26±858.71 16.90±24.61 9 (34.6)
48.23±16.35 31 (41.9)‡‡ 23.87±3.09 84.38±14.02 84.70±14.15 1.54±1.21 23.11±2.03††,II,¶¶ 23.08±1.85††,II,¶¶ 0.49±0.50 27/47 (36.5) 7.27±17.02 37/37 (50.0)II 363.96±278.10II 539.42±925.76 13.39±18.43 17 (23.0)††
47.80±15.74 21 (38.2)§§ 23.97±3.45 85.59±15.77‡,§§ 85.84±15.74‡,§§ 1.75±1.09 20.95±3.72§§,†† 21.69±3.73§§,†† 4.20±2.91 28/27 (50.9) 6.01±13.50 27/28 (49.1)¶ 341.07±394.61¶ 337.30±387.44 13.58±20.69 26 (47.3)††,§§
52.62±16.58 38 (69.1)§,‡‡,§§ 24.50±3.38 78.80±15.88§§ 78.51±15.31§§ 8.11±5.03 23.33±1.81§,**,§§ 23.53±1.78§,**,§§ 0.45±0.50 25/30 (45.5) 7.92±12.55 26/29 (47.3)** 488.90±650.44** 540.91±960.14 19.84±27.63 12 (21.8)§§
0.013 0.007 0.727 0.030 0.021 Not done
